Differentiated secondary index maintenance in log structured nosql data stores

Abstract

There is provided a method for operating multi-node data stores. A data table is stored in a first computing node and an index table is stored in a second computing node. The index table provides keys used for accessing data in the first computing node and other multi-node data stores. Operations that update or read the data table accessed from the first computing node and the index table accessed from the second computing node are performed. The operations optimize between latency in updating or reading the data table and the index table and data consistency maintained between data entries in the data table and data entries pointed by indices in the index table

Description

BACKGROUND[0001]This disclosure relates generally to data storage, and particularly to a multi-node data store.BACKGROUND OF THE INVENTION[0002]A data store refers to a data repository that uses a database, e.g., IBM® DB2®, etc., to manage data stored in the data repository. A data store may include a plurality of computing nodes, each of which uses a database management system to management data stored in a corresponding computing node. In recent years, scale-out data stores, referred as NoSQL data stores, are gaining attraction to support high-traffic Internet applications, e.g., yelp.com. A NoSQL data store is a class of database management systems that do not use a relational database model. A category of NoSQL data stores includes Log Structured Merge (LSM) Tree which is optimized for writing of data and MapReduce for scanning of data but is not optimized for point queries, e.g., a query directed to a specific datum. Examples of NoSQL data stores include, but are not limited to...

AI Technical Summary

Benefits of technology

The patent describes a way to make point queries faster in NoSQL data stores by using a secondary, global index that is managed by multiple region servers. This index avoids broadcasting queries to every data partition, making it more robust and efficient. The index can have multiple consistency levels that allow for different tradeoffs between accuracy and latency depending on the workload. This approach helps achieve faster processing times while maintaining data consistency.

Problems solved by technology

While these NoSQL data stores are a great fit for high-scale, low-complexity applications, as these applications get more complex, a lack of basic database functionality, e.g., secondary indexes, has become a stumbling factor.

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